ggplot() +
geom_function(fun = ~ 0.5*exp(-abs(.x)))
6 F
6.1 geom_function
6.1.1 Package
ggplot2 (Wickham 2016)
6.1.2 Description
Computes and draws a function as a continuous curve.
6.1.3 Understandable aesthetics
required aesthetics
x
y
optional aesthetics
alpha, colour, group, linetype, linewidth
6.1.4 The statistical transformation to use on the data for this layer
stat_prefix
6.1.5 See also
6.1.6 Example
6.2 geom_freqpoly
6.2.1 Package
ggplot2 (Wickham 2016)
6.2.2 Description
Visualise the spread of a single continuous variable by partitioning the x-axis into bins and mapping the frequency of observations within each bin.
6.2.3 Understandable aesthetics
required aesthetics
x
y
optional aesthetics
alpha, colour, group, linetype, linewidth
6.2.4 The statistical transformation to use on the data for this layer
stat_bin for a continuous x variable
stat_count for a discrete x variable
6.2.5 See also
6.2.6 Example
worldbankdata |>
ggplot(aes(x=Electricity, col=Income)) +
geom_freqpoly()
6.3 geom_flag
library(ggimage)
worldbankdata.flag <- worldbankdata |>
filter(Country %in% c("France", "Sweden", "Norway", "Germany", "Switzerland")) |>
filter(Year == 2000)
worldbankdata.flag$code.flag <- c("FR", "SE", "NO", "DE", "CH")
worldbankdata.flag |>
ggplot(aes(y = Country, x= Electricity)) +
geom_col(stat = 'identity') +
geom_flag(y = -2, aes(image = code.flag)) +
coord_flip() 
Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.